New Relic Reliability Engineer study plan
New Relic Reliability Engineer · Give each week a clear focus.
8 weeks · About 6 hours per week
Application Performance Monitoring (APM 360)
Configure a New Relic APM agent on a local service and verify transaction traces, error traces, and service maps appear in the UI
Distinguish the roles of transactions, segments, spans, and distributed traces in APM 360 and explain when each view is appropriate
Create a custom instrumentation span in code and confirm it appears nested correctly in a distributed trace
Set up a synthetic multi-service traffic generator to produce realistic APM data for later weeks
Your checkpoint
A one-page reference diagram of APM 360 data model (transactions to spans to traces) plus a screenshot-free written walkthrough of one traced request through two services
Application Performance Monitoring (APM 360)
Interpret Apdex scores, throughput, error rate, and response time percentiles to diagnose a simulated performance regression
Configure error grouping rules and explain how error fingerprinting affects alert noise
Configure browser and mobile agent instrumentation to connect front-end and back-end telemetry
Write three NRQL queries that isolate slow transactions by service and operation
Your checkpoint
A written incident analysis of a seeded latency regression identifying root cause from APM metrics, traces, and error data, with supporting NRQL queries
Digital Experience Monitoring
Deploy a browser agent on a test page and verify Core Web Vitals and AJAX call capture
Configure a synthetic monitor (scripted and API) and interpret its results against real user monitoring data
Differentiate real user monitoring, synthetic monitoring, and session replay use cases in Digital Experience Monitoring
Correlate a slow front-end page load with back-end APM traces using distributed tracing context
Your checkpoint
A comparison table mapping three Digital Experience Monitoring capabilities to the questions each answers, backed by data captured from your own test page
AI and Intelligent Automation
Explain how New Relic AI features surface anomalies and suggested root causes, and identify their limitations
Configure anomaly detection thresholds on at least two entities and observe alert behavior under injected load
Use applied intelligence features to group related incidents and describe how correlation reduces alert fatigue
Draft a decision checklist for when to trust automated root-cause suggestions versus manual investigation
Your checkpoint
A written evaluation of one AI-generated insight against manual investigation, documenting agreements, discrepancies, and confidence reasoning
Infrastructure Monitoring
Install the infrastructure agent on a host and verify CPU, memory, disk, and network metrics appear
Configure an infrastructure integration (for example, a database or message broker) and validate its metrics
Write NRQL alert conditions on infrastructure metrics and tune thresholds to avoid flapping
Explain how entity relationships link hosts to APM services and use them to trace an issue across layers
Your checkpoint
An infrastructure health dashboard definition plus a short write-up of one cross-layer investigation from host metric to APM symptom
Log Management
Forward application logs to New Relic and verify correlation with APM transactions via trace context
Write NRQL queries using log parsing, filtering, and aggregation functions to find error patterns
Configure a log-based alert and explain how log sampling and retention affect alert reliability
Design a log attribute schema that supports correlation, search, and cost control
Your checkpoint
A log correlation demo write-up showing one error found in logs, traced to an APM transaction, with the NRQL used at each step
Platform Capabilities (Alerts, Dashboards, OpenTelemetry, Fleet Control)
Build alert policies with multi-condition and multi-location configurations and document escalation logic
Create dashboards with linked entities, variables, and drill-down paths suitable for an on-call audience
Instrument a service with OpenTelemetry and send data to New Relic, explaining how OTLP ingestion differs from agent-based instrumentation
Describe Fleet Control use cases for managing agent configuration at scale
Your checkpoint
A production-ready alert policy and dashboard package (exported JSON) with a written runbook explaining each alert's intent and tuning rationale
Platform Capabilities (Alerts, Dashboards, OpenTelemetry, Fleet Control) & Security and Risk Prioritization
Prioritize vulnerabilities surfaced by security monitoring using entity context, exploitability, and blast radius
Configure a security-focused alert and explain how risk scoring influences prioritization decisions
Run a full timed practice assessment across all seven domains and log every missed concept
Close knowledge gaps identified by the practice assessment with targeted review of the two weakest domains
Your checkpoint
A scored practice assessment with a gap-closure log listing each missed concept, the corrected understanding, and the source used
Milestones
Week 2: Can diagnose a latency regression end-to-end from APM metrics, traces, and errors without external help, and explain Apdex and percentile tradeoffs aloud in under five minutes
Week 4: Has working browser and synthetic monitors feeding data and can articulate the limits of AI-driven root-cause suggestions with a concrete example
Week 6: Can move from a host metric to an APM symptom to a correlated log line in one investigation and explain entity relationships along the way
Week 8: Scores at least 80 percent on a timed all-domain practice assessment and has a written gap-closure log for every missed concept